Title :
Mining the Largest Quasi-clique in Human Protein Interactome
Author :
Bhattacharyya, Malay ; Bandyopadhyay, Sanghamitra
Author_Institution :
Machine Intell. Unit, Indian Stat. Inst., Kolkata, India
Abstract :
A clique is a complete subgraph of a graph. Often, a clique is interpreted as a dense module of vertices within a graph. However, in many real-world situations, the classical problem of finding a clique is required to be relaxed. This motivates the problem of finding quasicliques that are almost complete subgraphs of a graph. In sparse and very large scale-free networks, the problem of finding the largest quasi-clique becomes hard to manage with the existing approaches. Here, we propose a heuristic algorithm in this paper for locating the largest quasi-clique from the human protein-protein interaction networks. The results show promise in computational biology research by the exploration of significant protein modules.
Keywords :
biology computing; complex networks; data mining; graph theory; computational biology; graph; heuristic algorithm; human protein interactome; human protein-protein interaction networks; quasi-cliques; scale-free networks; subgraphs; Adaptive systems; Computational biology; Computer network management; Heuristic algorithms; Humans; Intelligent systems; Machine intelligence; Organisms; Proteins; Web sites;
Conference_Titel :
Adaptive and Intelligent Systems, 2009. ICAIS '09. International Conference on
Conference_Location :
Klagenfurt
Print_ISBN :
978-0-7695-3827-3
DOI :
10.1109/ICAIS.2009.39